Table 1.

Multilevel regression results estimating support for alcohol control policies

Variable	Support for enforcement (n = 785) b (SE)	Support for new policies (n = 785) b (SE)
Intercept, γ00	8.176 (0.123)	5.336 (0.154)
Alcohol mentioned, γ10	0.388 (0.141)**	0.122 (0.181)
Other accident, γ01	0.062 (0.173)	0.096 (0.213)
Violent crime, γ02	0.140 (0.173)	0.727 (0.214)***
News attention, β2	0.153 (0.028)***	0.173 (0.036)***
Sex, β3	0.342 (0.144)*	0.614 (0.184)***
Age, β4	0.031 (0.004)***	0.025 (0.006)***
Alcohol use, β5	-0.529 (0.080)***	-0.989 (0.102)***
Level 1 R2	.173	.185

Notes: “Alcohol mentioned” is coded -0.5 for the alcohol not mentioned condition and 0.5 for the alcohol mentioned condition and was estimated as a random effect across stories. “Other accident” and “violent crime” are dummy variables (0/1) coding topic, with the motor vehicle accident topic condition as the reference group. All other variables in the model are grand mean centered. Level 1 R² is the proportional reduction in the Level 1 residual variance when all seven predictors are entered into a model containing only the random intercept. All coefficients are unstandardized. The covariance between the random intercept and random alcohol-mentioned effect was freely estimated. Degrees of freedom for alcohol mentions and the intercept are 59 and 57, respectively. Degrees of freedom for all other effects are 661.

^*p <.05;

^**p <.01;

^***p < .001.